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Italian fruits and vegetables have lost ground in terms of competitiveness… On both domestic and international markets Why: Extreme fragmentation of the business fabric Extreme fragmentation of distribution channels Delayed enforcement of UE quality regulations High quality of imported produce

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Therefore producers should put a greater emphasis on post-harvest operations Correctly performed and optimized post- harvest operations result in a remarkable increase in produce quality What is more, post- harvest technology is continuously developing

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Fruits and Vegetables Ranking Ranking essentially relies on: size, weight, colour (extrinsic features) Today sophisticated ranking systems are being developed to assess also fruit intrinsic features (pulp firmness, degree of maturation, chemical characteristics, etc..) *Few experimental data are available about the actual operational parameters of the different systems used to carry out the most important of post- harvest operation: grading

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GRADING, Under EU Fruits and Vegetables Commercialization Regulations: grading is determined by the measurement of maximum chord of the normal section of the fruit polar axis. In fruits and vegetables packhouses grading is performed by continuosly evolving special systems.

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Mechanical systems are still utilized which are based on elements including: Vibrating meshes with gauged holes Properly distanced tilting rollers

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However mechanical systems are poorly accurate…. Diverging Conveyors System Do not allow for a fast change in sorting schemes according to the different fruits to be sorted; Need a lot of labour to make up for grading errors; Have a limited operation capacity and a remarkable overall dimension. Are losing ground to electronic systems.

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Electronic graders are in most cases based on vision technology: a digital image processor analyzes fruit images acquired by one or more videocameras to obtain the geometric sizes required for correct grading.

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Many are the optical grader models produced today which are likely to meet the different needs of the most diverse businesses. Producers declare a grading accuracy within 1 mm also at a conveyor speed of 11 fruits/sec. But is this speed real for all fruits and at all speeds? Therefore it was decided to study the operation of two optical graders operating in two modern plants in order to obtain data on their efficiency on the basis of some preliminary tests performed with oranges, lemons and table tomatoes

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The study focused on the operation features and on the yield quality of two plants: A and B (*) the plant is made up of two identical and independent sorting lines PlantProducerModel Lanes (n.) Drop Locations Sorting Device AMaxfrut Maxsorter v Videocamera B*Unitec Unical 600T–OC 630Videocamera

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TEST METHODOLOGIES The operation capacity of the two graders under study was measured by assessing the filling percentage of those sectors of the roller conveyors destined to held fruits and by applying the following relation: C = V x 3600 x R x n [fruits/ h], where: C = operation capacity; V = speed, as expressed in the sectors/s (= fruits/s, = 0.1 m/s); R = percentage of sectors filled; n = number of lanes.

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TESTS METHODOLOGIES Fruits were numbered with a manual gauge. They were then placed, one by one, on the conveyors of Graders A and B and advanced to pass thruogh a vision chamber. Ten repeats were made for each fruit. Tests were repeated at three speeds of the conveyor for A: 0.6 m/s, 0.8 m/s and 1.1 m/s; and at two speeds for B: 0.8 m/s e 1.1 m/s. Data from the two graders were compared with the measurements made with the manual gauge.

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RESULTS AND REMARKS Operation capacity of the graders under study Grader Lanes (n°) Fruits processed Speed (m/s) Operation capacity (fruits/h) Operation capacity (t/h) Workers (n°) A4oranges 0.880, , B*6lemons 0.812, , B*6Tomatoes 0.812, , * Data of one of the two graders of Plant B Graders A and B where found to have a filling percentage of the conveyor sectors destined to fruits of about 70% which remained constant at different operation speeds. Operation capacity is extremely elevated.

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RESULTS AND REMARKS Grading accuracy tests Data from the two graders were compared with the measurements made with the manual gauge. Data were analyzed taking into account the absolute error (Ae), i.e. the difference between the fruit "equatorial" diameter calculated by the grader and that measured by the manual gauge. Ae = Cm – Cr [mm] where: Cm = maximum chord of the section normal to the friut longitudinal axis measued by the optical device; Cr = maximum chord of the section normal to the friut longitudinal axis measued by the manual gauge. The influence on Ae of both fruits speed and gauge was assessed.

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RESULTS AND REMARKS Average standard deviation and variation coefficient (C.V.) for graders A and B - Test repeats highlighted a good level of homogeneity in the diameter readings " made on the same samples during successive passings before the videocamera, as can be inferred by the standard deviation average and the variation coefficient given in the Table below. SpeedGrader AGrader B (m/s)St. Dev.V.C.St. Dev.V.C.St. Dev.V.C lemonstomatoes

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CONCLUSIONS The machines under study are in addition characterized by the possibility of varying the grading schemes selected by simply acting on the control panel. They are also able to minimize fruit damage thus responding to the demand of quality on the part of consumers. Accuracy and the possibility of processing different types of fruits result in a prolonged use of the graders throughout the year thus reducing both labour and post-harvest operation costs. In order to obtain better results optical graders need careful upkeep and calibration as well as well skilled workers trained to manage at best the control systems of their optical/electronic devices. The selection of graders must be carefully weighed based on their own technical specifications and on the needs of their users.